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Targetlynx

Manufactured by Waters Corporation
Sourced in United States, United Kingdom

TargetLynx is a software package developed by Waters Corporation for the analysis and quantification of target compounds in complex samples using liquid chromatography-mass spectrometry (LC-MS) data. The software provides features for data processing, method development, and reporting.

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72 protocols using targetlynx

1

LC-MS Targeted Data Analysis Workflow

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The LC–MS equipment was controlled using MassLynx (v4.1, Waters Corp., Milford, MA, USA) configured with the Waters Pump Control (Waters Corp., Milford, MA, USA) LC-pump drivers loaded to facilitate control of multiple pumps. The TargetLynx (v4.1, Waters Corp., Milford, MA, USA) module for MassLynx was used to determine peak areas and retention times in the targeted analysis. Any further data analysis was performed either in Excel 2016 (Microsoft, Redmond, WA, USA) or in the R statistical language environment (v3.6.1). Conversion of Waters proprietary data format into NetCDF was performed using Databridge (v3.5, Micromass UK Ltd., Manchester, UK). Peak picking, retention time alignment, and correspondence were performed using the R-package XCMS (v3.12.0) [33 (link)]. Multivariate analysis was performed using the R-package ropls (v1.22.0). Batch and drift correction was performed using the batchCorr R-package (v0.2.5) [34 (link)].
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2

Phenolic Compound Analysis by UPLC-MS

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The analysis and characterization of phenolic compounds were carried out following the protocol described elsewhere66 (link), yet with a simplified methanol–water-based sample extraction57 (link). For this assessment, a UPLC Waters Acquity (Milford, MA, USA) coupled to a Waters Xevo TQMS mass spectrometer (Milford, MA, USA) was employed. Each compound was analyzed with optimized MRM conditions as previously described66 (link). The softwares Waters MassLynx 4.1 and TargetLynx were employed to process the obtained phenolic data previously characterized on the base of reference compounds. The results were expressed as mg/kg of fresh weight.
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3

Quantification of Vitamin D Metabolites

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Vitamin D metabolites were extracted from donor serum (0.2 mL) or placental tissue homogenates as described previously [26 ]. Resulting samples were reconstituted in 125 μL water/methanol (50/50%) for LC-MS/MS analysis as previously described [26 ] using a Waters ACQUITY ultra performance liquid chromatography [uPLC] coupled to a Waters Xevo TQ-S mass spectrometer [Waters, Manchester, UK]). Analysis was carried out in multiple reaction monitoring (MRM) mode, with optimised MRM transitions for each analyte as described previously [26 ]. External quality control (QC) samples (LGC Standards, Teddington, UK) for 25(OH) D3 and 25(OH)D2 were used to assess accuracy and precision within batch runs. QCs across different concentration ranges to determine inter- and intra-day accuracy and precision for each analyte were as described previously [26 ]. Data analysis was performed with Waters Target Lynx.
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4

Quantifying Myr p Allergen Peptides

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To assess Myr p allergen peptide changes, the 25 μg/mL venom samples were analysed by UPLC-UV using an Acquity H-series UPLC (Waters Corporation, Milford, Massachusetts, USA) coupled to an Acquity Photo Diode Array (PDA) detector. An Acquity UPLC BEH C18 column (2.1 x 100 mm x 1.7 μm particles) held at 40 °C was used. The mobile phase flow rate was 0.35 mL/min and the solvent system was water:acetonitrile:1% trifluoroacetic acid in water (80:12:8, v/v/v) to (24:68:8, v/v/v) in a linear gradient over 12 min before re-equilibration for 3 min to initial conditions. Triplicate injections of 40 μL were made and data for quantitative measurements of peak areas corresponding to the Myr p 1–3 allergen peptides were extracted at 220 nm. Under these conditions Myr p 2 eluted at 7.22 min, Myr p 3 at 7.52 min, and Myr p 1 at 8.39 min (Fig S1). Data were analysed using Waters MassLynx and TargetLynx software. The mean peak area for each allergen peptide was calculated and the analysis of remaining concentration of the allergen peptides was calculated as a percentage relative to baseline samples.
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5

Quantitative Intracellular Metabolomics

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TopSpin v4.1.1 (Bruker, United States) was used to process all NMR spectra. After Fourier transformation, phase, and baseline correction of the NMR spectra, extracellular glucose and lactate concentration were quantified based on ERETIC2 function, with creatine as the external standard. All processing of MS-based data was performed in the TargetLynx application manager of Masslynx 4.1 (Waters Corporation, United States). All response factors are corrected by the corresponding U13C(15N)-isotopologue. Absolute intracellular metabolites concentrations were normalized based on dilution factors during sample preparation and to cell density and average cell volume.
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6

Quantification of Analytes Using UPLC-MS/MS

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UPLC–MS/MS data were acquired with MassLynx v4.1 software, while quantification processing was performed with TargetLynx (Waters, Milford, MA, USA). Excel (Microsoft 2018, Washington, DC, USA), SPSS Statistics (IBM, version 27, Armonk, NY, USA), and GraphPad prism 8 (2019, San Diego, CA, USA) were used for general descriptive statistics. Data (concentration values) were log-transformed prior to performing Spearman correlation and principal component analysis (PCA). A t-test was used to test the significance of differences. The probability value of p < 0.05 was set for statistical significance. Values below the limits of detection (LODs) were substituted with a value equal to the LOD of the respective target analyte divided by a factor of √2. Concentrations were reported as ng/g wet weight (w.w.).
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7

Comprehensive Metabolomics Data Processing

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All multivariate raw data were processed using Progenesis QI (Nonlinear dynamics, Newcastle UK) which performed run alignment, peak picking, adduct deconvolution and eventual feature (linked mass/retention time pairs) database searching. Principle component analysis (PCA), using Pareto scaling, was performed using Ezinfo (Umetrics, Umeå SE) in order to visualise group separation, and orthogonal partial least squared discriminate analysis (OPLS-DA) to identify significant features. In the assessment of chromatographic performance, specific target compounds were extracted and integrated using TargetLynx (Waters Corporation, Milford USA). The databases used to generate potential identifications were the Metlin MS/MS (Scripps Institute, CA, USA) and the human metabolome database (HMDB) (Wishart et al. 2018 (link)) with precursor and fragmentation ion accuracy set to 10 ppm. For CCS measurements, the IROA CCS database (Waters Corporation, Milford USA) with a tolerance to the database value of 2.5% was used.
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8

Amino Acid Quantification in Tomato Tissues

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Tomato root and leaf tissues (50 mg/sample) were used for each replicate. Three independent experiments were performed. For each time/concentration point, analyses were done in triplicate. Amino acids were quantified according to the procedure described previously (Zwighaft et al., 2015 (link)). The concentrations based on standard curves were calculated using TargetLynx (Waters). The amino acid amount in leaves of plants regularly watered at the first sampling time (10 dd) was considered as 100; leaf and root amino acids levels in all plants used throughout the experiments were estimated relative to this value.
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9

Quantitative Analysis of Antiparasitic Drugs

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The data processing was performed with TargetLynx, available in the MassLynx software (version 4.1, Waters Corp.) by integration of the area under the specific MRM chromatograms in reference to the integrated area of the isotope-labeled analogue.
The calibration curves were constructed using concentrations ranging from 0.2–12.8 µmol/L of ABZ-SOX, respectively 0.125–8.0 µmol/L of ABZ-SON by using linear regression with a 1/x weighting factor. Mean values and standard deviations were calculated in Excel.
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10

Targeted MS Data Extraction and Analysis

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The targeted MS data was exported from
the TargetLynx (Waters) software into a Microsoft Excel spreadsheet
where data was reported, sample by sample, for each transition. Each
transition was designated as “compound” by the TargetLynx
software. A Matlab (Mathworks) script was implemented to extract information
(such as relative percentages) from samples and pivot tables in a
fashion that allows easier post processing in Microsoft Excel.
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